Analyzing the dynamic ride-sharing potential for shared autonomous vehicle fleets using cellphone data from Orlando, Florida

Abstract

Transportation network companies (TNCs) are regularly demonstrating the economic and operational viability of dynamic ride-sharing (DRS) to any destination within a city (e.g., uberPOOL or Lyft Line), thanks to real-time information from smartphones. In the foreseeable future, fleets of shared automated vehicles (SAVs) may largely eliminate the need for human drivers, while lowering per-mile operating costs and increasing the convenience of travel. This may dramatically reduce private vehicle ownership resulting in extensive use of SAVs. This study anticipates DRS matches across different travelers and identifies optimum fleet sizes required using AirSage's cellphone-based trip tables across 1267 zones over 30 days. Assuming that the travel patterns do not change significantly in the future, the results suggest significant opportunities for DRS-enabled SAVs. Nearly 60% of the single-person trips could be shared with other individuals traveling solo and with less than 5 min of added travel time (to arrive at their destinations), and this value climbs to 80% for 15 to 30 min of added wait or travel time. 60,000 SAVs will be required to meet nearly 50% of Orlando's 2.8 million single-traveler trips each day. With maximum ride-sharing delays of 15 minutes, and when focused on serving solo travelers, the average SAV is able to serve 25 person-trips per day, reducing parking demands while filling up passenger vehicle seats.